Quantitative analysis of microscopic<scp>X</scp>‐ray computed tomography imaging: Japanese quail embryonic soft tissues with iodine staining
Bibliographic record
Abstract
Rapid three-dimensional imaging of embryos to better understand the complex process of morphogenesis has been challenging. Recently introduced iodine staining protocols (I2 KI and alcoholic iodine stains) combined with microscopic X-ray computed tomography allows visualization of soft tissues in diverse small organisms and tissue specimens. I2 KI protocols have been developed specifically for small animals, with a limited number of quantitative studies of soft tissue contrasts. To take full advantage of the low X-ray attenuation of ethanol and retain bound iodine while dehydrating the specimen in ethanol, we developed an ethanol I2 KI protocol. We present comparative microscopic X-ray computed tomography analyses of ethanol I2 KI and I2 KI staining protocols to assess the performance of this new protocol to visualize soft tissue anatomy in late stage Japanese quail embryos using quantitative measurements of soft tissue contrasts and sample shrinkage. Both protocols had only 5% shrinkage compared with the original harvested specimen, supporting the use of whole mounts to minimize tissue shrinkage effects. Discrimination within and among the selected organs with each staining protocol and microscopic X-ray computed tomography imaging were comparable to those of a gray scale histological section. Tissue discrimination was assessed using calibrated computed tomography values and a new discrimination index to quantify the degree of computed tomography value overlaps between selected soft tissue regions. Tissue contrasts were dependent on the depth of the tissue within the embryos before the embryos were saturated with each stain solution, and optimal stain saturations for the entire embryo were achieved at 14 and 28 days staining for I2 KI and ethanol I2 KI, respectively. Ethanol I2 KI provided superior soft tissue contrasts by reducing overstaining of fluid-filled spaces and differentially modulating staining of some tissues, such as bronchial and esophageal walls and spinal cord. Delineating the selected soft tissues using optimal threshold ranges derived from the quantitative analyses of the contrast enhancement in optimally stained embryos is possible. The protocols presented here are expected to be applicable to other organisms with modifications to staining time and contribute toward rapid and more efficient segmentation of soft tissues for three-dimensional visualization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".